πŸ“Š KG-Eval Report

Multi-Dimensional Knowledge Graph Evaluation

πŸ“ˆ Performance Overview

πŸ”’

Scale & Richness

Measures the breadth and depth of extracted information
Entity Count
4,159
Total number of unique entities identified
Relationship Count
6,916
Total number of relationships extracted
Property Fill Rate
100.0%
Excellent Completeness of entity properties
Relationship Types
3862
Diversity of relationship types used
πŸ•ΈοΈ

Structural Integrity

Evaluates graph connectivity and topological health
Graph Density
1.6629
Excellent Ratio of actual edges to possible edges
Largest Connected Component
69.9%
Good Percentage of nodes in main connected component
Connected Components
1189
Number of disconnected graph components
Singleton Nodes
27.5%
Percentage of isolated nodes (lower is better)
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Semantic Quality

Assesses accuracy, consistency, and relevance of extracted knowledge
Entity Normalization Score
74.2%
Good Consistency in entity naming and representation
Factual Precision
πŸ€– 92.0%
LLM-evaluated factual accuracy of extracted information
Potential Alias Pairs
1073
Entity names that might refer to the same concept
Contextual Relevance
πŸ€– 26.0%
LLM-evaluated relevance to source context
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Efficiency

Measures effectiveness of text-to-knowledge transformation
Knowledge Density
17.98
Excellent Average knowledge elements per text chunk
Productive Source Ratio
100.0%
Excellent Percentage of source texts that contributed to KG
Average Text Length
1085
Average length of source text chunks
Source Coverage
0.0%
Percentage of source content linked to KG elements

πŸ’‘ Recommendations for Improvement

  • Review and merge potential entity aliases to improve consistency